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Comprehensive analysis of computational methods for predicting anti-inflammatory peptides
Inflammation is a biological resistant response to harmful stimuli, such as infection,
damaged cells, toxic chemicals, or tissue injuries. Inflammation eradicates pathogenic …
damaged cells, toxic chemicals, or tissue injuries. Inflammation eradicates pathogenic …
Recent advances in machine learning-based models for prediction of antiviral peptides
Viruses have killed and infected millions of people across the world. It causes several
chronic diseases like COVID-19, HIV, and hepatitis. To cope with such diseases and virus …
chronic diseases like COVID-19, HIV, and hepatitis. To cope with such diseases and virus …
iAFPs-EnC-GA: identifying antifungal peptides using sequential and evolutionary descriptors based multi-information fusion and ensemble learning approach
Fungal infections have become a serious health concern for human beings worldwide.
Fungal infections usually occur when the invading fungus appear on a particular part of the …
Fungal infections usually occur when the invading fungus appear on a particular part of the …
XGB-DrugPred: computational prediction of druggable proteins using eXtreme gradient boosting and optimized features set
Accurate identification of drug-targets in human body has great significance for designing
novel drugs. Compared with traditional experimental methods, prediction of drug-targets via …
novel drugs. Compared with traditional experimental methods, prediction of drug-targets via …
AFP-CMBPred: Computational identification of antifreeze proteins by extending consensus sequences into multi-blocks evolutionary information
In extremely cold environments, living organisms like plants, animals, fishes, and microbes
can die due to the intracellular ice formation in their bodies. To sustain life in such cold …
can die due to the intracellular ice formation in their bodies. To sustain life in such cold …
AIPs-DeepEnC-GA: Predicting anti-inflammatory peptides using embedded evolutionary and sequential feature integration with genetic algorithm based deep …
Inflammation is a biological response to harmful stimuli including infections, damaged cells,
tissue injuries, and toxic chemicals. It plays an essential role in facilitating tissue repair by …
tissue injuries, and toxic chemicals. It plays an essential role in facilitating tissue repair by …
Deep-AntiFP: Prediction of antifungal peptides using distanct multi-informative features incorporating with deep neural networks
World widely, Fungal infections have become a serious issue for human beings. Fungal
infections normally happen once invading fungus appear on a specific area of the body and …
infections normally happen once invading fungus appear on a specific area of the body and …
iHBP-DeepPSSM: Identifying hormone binding proteins using PsePSSM based evolutionary features and deep learning approach
Hormone binding proteins (HBPs) are soluble carrier proteins that can non-covalently and
selectively interact with the human hormone. HBPs plays a significant role in human life, but …
selectively interact with the human hormone. HBPs plays a significant role in human life, but …
DBP-CNN: Deep learning-based prediction of DNA-binding proteins by coupling discrete cosine transform with two-dimensional convolutional neural network
To improve the prediction of DNA-binding Proteins (DBPs), this paper presents a deep
learning-based method, named DBP-CNN. To efficiently extract the important features, we …
learning-based method, named DBP-CNN. To efficiently extract the important features, we …
A selective ensemble preprocessing strategy for near-infrared spectral quantitative analysis of complex samples
X Bian, K Wang, E Tan, P Diwu, F Zhang… - … and Intelligent Laboratory …, 2020 - Elsevier
Preprocessing of raw near-infrared (NIR) spectra is typically required prior to multivariate
calibration since the measured spectra of complex samples are often subject to …
calibration since the measured spectra of complex samples are often subject to …